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PinterestData Scientist II, ML Infrastructure
Pinterest operates a digital platform that helps users discover creative ideas and plan inspiration for their lives. The company is currently hiring a Data Scientist II,…
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About This Role
Pinterest operates a digital platform that helps users discover creative ideas and plan inspiration for their lives. The company is currently hiring a Data Scientist II, ML Infrastructure to work in San Francisco on an on-site basis. This role centres on advancing the science and systems behind machine learning measurement, feature understanding, and causal inference at scale. The position suits an enthusiastic individual contributor who wants to drive foundational innovations,…
Job Description
Pinterest operates a digital platform that helps users discover creative ideas and plan inspiration for their lives. The company is currently hiring a Data Scientist II, ML Infrastructure to work in San Francisco on an on-site basis. This role centres on advancing the science and systems behind machine learning measurement, feature understanding, and causal inference at scale. The position suits an enthusiastic individual contributor who wants to drive foundational innovations, own end-to-end design of production machine learning systems, and partner cross-functional to turn research into platform capabilities.
The chosen candidate will translate research-grade data science workflows into production pipelines, apply and productionize causal inference methods, and build self-serve tooling for scale. Day-to-day responsibilities involve developing data-driven frameworks utilizing metadata and engagement signals, building centralized platform tooling, and establishing reusable patterns for other teams. The position requires a professional capable of reasoning about machine learning models from first principles while maintaining software development best practices.
Responsibilities
- Translate research-grade data science workflows into production machine learning pipelines using Airflow, WandB, and Ray
- Apply and productionize causal inference methods including propensity scoring, IPW, and TMLE
- Build self-serve tooling for scaling causal insights among non-experts
- Partner with machine learning engineers and product teams to enhance tooling, metrics, and measurement methods
- Build data-driven frameworks leveraging metadata and engagement signals to improve platform efficiency
- Design and build centralized machine learning platform tooling to support feature and model creation, evaluation, and trust
Requirements
- Possess at least two years of hands-on experience as an applied scientist, machine learning engineer, research scientist, or software engineer with significant machine learning production background
- Demonstrate strong Python programming skills
- Bring experience using PyTorch or equivalent deep learning frameworks
- Show familiarity with distributed compute systems like Spark or Ray
- Apply software development best practices covering version control, code review, and reproducible machine learning pipelines
- Use workflow management tools such as Airflow, Prefect, or Jenkins for reliable pipeline orchestration
- Attend the office for in-person collaboration three to five times per quarter while residing anywhere in the United States
Qualifications
- Experience using Ray specifically
- Hold a Bachelor’s or Master’s degree in Computer Science or a relevant field, or possess equivalent experience
Core Skills
Benefits
- Eligible for equity
Frequently Asked Questions
What is the location and remote policy for this role?
This position is based in San Francisco with an on-site requirement to visit the office for in-person collaboration three to five times per quarter, allowing employees to live anywhere in the country.
Does the posting specify a salary for this position?
Yes, the United States base salary range listed for this position is $114,297 to $235,319 USD, and the role is also eligible for equity.
What type of employment is this?
The employment type is full-time.
Is relocation assistance available?
No, this position is not eligible for relocation assistance.
What are the core experience requirements?
Candidates must have at least two years of hands-on experience as an applied scientist, machine learning engineer, research scientist, or software engineer with substantial production experience, along with strong Python skills and deep learning framework familiarity.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.